Condition monitoring (CM) is used to assess the health status of wind turbines (WT) by detecting turbine failure and predicting maintenance needs. However, fluctuating operating conditions cause variations in monitored features, therefore increasing the difficulty of CM, for example, the frequency-domain analysis may lead to an inaccurate or even incorrect prediction when evaluating the health of the WT components. In light of this challenge, this paper proposed a method for the health evaluation of WT components based on vibration signals. The proposed approach aimed to reduce the evaluation error caused by the impact of the variable operating condition. First, the vibration signal was decomposed into a set of sub-signals using variational mode decomposition (VMD). Next, the sub-signal energy and the probability distribution were obtained and normalized. Finally, the concept of entropy was introduced to evaluate the health condition of a monitored object to provide an effective guide for maintenance. In particular, the health evaluation for CM was based on a performance review over a range of operating conditions, rather than at a certain single operating condition. Experimental investigations were performed which verified the efficiency of the evaluation method, as well as a comparison with the previous method.

The modeling of the minimum fluidization velocity (U_0mf) and the incipient fluidization pressure drop (ΔP_mf) is a valuable research topic in the fluidization field. In this paper, first, a series of experiments are carried out by changing the particle size and material mass to explore their effects on U_0mf and ΔP_mf. Then, an Ergun equation modifying method and the dimensional analysis method are used to obtain the modeling correlations of U_0mf and ΔP_mf by fitting the experimental data, and the advantages and disadvantages of the two methods are discussed. The experimental results show that U_0mf increases significantly with increasing particle size but has little relationship with the material mass; ΔP_mf increases significantly with increasing material mass but has little relationship with the particle size. Experiments with small particles show a significant increase at large superficial gas velocity; we propose a conjecture that the particles’ collision with the fluidization chamber’s top surface causes this phenomenon. The fitting accuracy of the modified Ergun equation is lower than that of the dimensionless model. When using the Ergun equation modifying method, it is deduced that the gas drag force is approximately 0.8995 times the material total weight at the incipient fluidized state.